LÍNEA DEL TIEMPO
Estudiante 3 Modelo Teórico Humanista
6. Con base en el modelo de formación
Any new or modified traffic control system should satisfy a goal or set of goals. The goal may explicitly state: reduce congestion in the core area of a city by minimizing stops and delays or pledge increase accessibility to downtown business. Goals may be easy to state, but difficult to measure.
Measures of effectiveness (MOE) provide a quantitative basis for determining the capacity of traffic control systems and their strategies to attain the desired goals. To successfully determine goal attainment, the MOEs must relate to the goals. Also, with no comparative analyses, measures must be compared with baseline values to determine the quality of goal attainment. Other desirable criteria for selecting MOEs include:
• Simplicity within the constraints of required precision and accuracy,
• Sensitivity to relatively small changes in control strategy implementation, and • Measurability on a quantitative scale within reasonable time, cost, and
manpower budgets.
Common measures of effectiveness include: • Total travel time,
• Total travel,
• Number and percentage of stops, • Delay,
• Average speed, • Accident rate, and • Throughput.
These measures of effectiveness indicate the improvement in efficiency of traffic flow resulting from control.
Table 3-31 describes these MOEs and their calculation.
Several other important MOEs can be derived from those in the Table. Gasoline consumption and emissions, for example, can be computed from total travel time, stops, and delay (93).
Table 3-31. Measures of Effectiveness (MOE).
MOE Description Calculation
Total Travel Time A primary MOE for evaluating freeway and urban street control systems and strategies. Expressed in vehicle-hours (veh-hr), it represents the product of the total number of vehicles using the roadway during a given time period and the average travel time of the vehicles.
The average travel time, ttj, in hours over a roadway section is:
j j j u X tt = (3.25) Where:
Xj = Length of roadway section, in mi (km) and
uj = Average speed of vehicles over roadway section j, in
mi/hr (km/hr)
Total travel time, TTTj, in veh-hr over section j is:
j j j j j j u X N tt N TTT = = (3.26) Where:
Nj = Number of vehicles traveling over section j, during
time period,
ttj = Average travel time of vehicles over roadway
section j, in hrs
Total travel time, TTT, in veh-hr, for all sections of a roadway is:
∑
= = K j j TTT TTT 1 (3.27) Where:Table 3-31. Measures of Effectiveness (MOE) (continued).
MOE Description Calculation
Total Travel Another common MOE used to evaluate traffic operations. Expressed in units of vehicle-miles (veh-mi) (vehicle-kilometers (veh-km)), it represents the product of the total number of vehicles using the roadway during a given time period and the average trip length of the vehicles.
The total travel, TTj, in veh-mi, over a roadway section j is: j j j X N TT = (3.28) Where:
Xj = Length of roadway section j, in mi (km)
Nj = Number of vehicles traveling over section j during time period, T
Equations 3.26 and 3.28 suggest that the total travel, TTj, in veh-mi (veh-km), over a roadway section j can be derived from total travel time and average speed for section j, as follows:
j j j TTT V TT = (3.29) Where:
TTTj = Total travel time for section j during time period, T, in veh-hr,
and
Vj = Average speed of vehicles over section j during time period, T,
in mi/hr (km/hr)
Total travel, TT, in veh-mi (veh-km), for all sections of a roadway is:
∑
= = K j j TT TT 1 (3.30) Where:Table 3-31. Measures of Effectiveness (MOE) (continued).
MOE Description Calculation
Number and Percentage of Stops
Evaluates the quality of flow on urban streets. Stops may be obtained by floating vehicle methods or by direct observation of the intersection. Traffic control systems may have the capability to compute stops.
The calculation of the number of stops on an approach to an intersection is determined by the relationship between detector actuations and signal timing. A typical time-space diagram for number of stops computations is presented in Figure 3-35. The number of stops per cycle is the number of detector actuations that occur between Tgc and Trc. Trc is the last time that a vehicle can cross the detector during the green interval, and still clear the intersection without stopping. The values for Tgc and Trc are based on predetermined vehicle trajectories between the detector and the intersection. In some algorithms for computing number of stops, these trajectories remain the same for all vehicles, while in others they vary according to the number of vehicles already stopped between the detector and intersection.
Delay Widely used MOE in traffic control. On urban arterials, delay is defined as the increase beyond a travel time corresponding to a baseline speed (a speed below which travel would be considered delayed).
For urban intersections, delay is commonly defined as the time lost at the intersection by those vehicles that are stopped. Box and Oppenlander describe a technique for manually obtaining stopped delay (94).
For urban arterials, baseline travel time subtracted from measured total travel time for the same time period. Where computer traffic control systems compute delay, Figure 3-35 illustrates the computation of stopped-vehicle delay. Assuming all stopped vehicles clear the intersection on the next green, the delay Di, in seconds, for the ith stopped vehicle is determined.
) ( ) ( i r i g i R tc T td T D = − − + − (3.31) Where:
R = Length of the red interval, in seconds
Tr = Time at which the red interval begins, in seconds
tci = Predicted time at which the ith vehicle would have reached the
intersection if it had not been stopped, in seconds
Tg = Time at which the next green interval beings, in seconds
tdi = Predicted time at which the ith vehicle clears the
Table 3-31. Measures of Effectiveness (MOE) (continued).
MOE Description Calculation
Delay (continued) Time, tci, is determined from the time, taj, at which the ith vehicle actuates the detector and a predetermined approach trajectory. Time, tdj, is determined from time, Tg, at which the next green interval begins and- a predetermined departure trajectory. Some algorithms used to compute stopped-vehicle delay provide for varying the predetermined approach and departure trajectories according to the number of vehicles already stopped. Assuming all stopped vehicles clear the intersection on the next green, total stopped-vehicle delay, D, in seconds, for a cycle is determined by:
∑
= = n i i D D 1 (3.32) Where:Di = The delay of the ith vehicle stopped during the cycle, in
seconds
n = The number of vehicles stopped during the cycle
Algorithms based on these concepts may be subject to the following additional sources of error:
• Vehicles making right-turns-on-red may not be properly accounted for
• The algorithm might not properly handle saturated intersections Average Speed One of the most descriptive variables of freeway
traffic flow. Point samples of average stream speeds or the speed traces of individual vehicles can locate problem areas and provide useful data for developing other performance measures (93).
Manually, by radar or laser guns. See Table 3-1 for calculations from system detectors.
Table 3-31. Measures of Effectiveness (MOE) (continued).
MOE Description Calculation
Accident Rate Accident rate improvement is a common goal for traffic control systems. Rates for intersections usually are expressed in terms of accidents per million entering vehicles. Freeway accident rates are often expressed in accidents per 100 million vehicle miles.
Box and Oppenlander describe techniques- for determining the statistical significance of accident data (94).
Throughput Although its dimension is equivalent to speed, throughput is usually used in a somewhat different way. Figure 3-36 shows plots of throughput for a baseline system (curve A) and an improved traffic control system (curve B). These plots represent a best mathematical fit of the data represented by individual sets of measurements. Throughput is represented by the slope of the line to a point on the curves. As traffic demand increases, the throughput begins to decrease.
This approach enables the traffic engineer to more precisely measure results relative to goals. For example, if the goal is to improve congested traffic conditions, examination of curve B in the congested region indicates only marginal improvement. This might lead the traffic engineer to consider strategies to specifically target to this region (section 3.8).
time of unit per hours Vehicle time of unit per km mi Vehicle Throughput= ( )
Figure 3-35. Time-space Diagram for Stop and Delay Computations for Urban Street Control.
In many cases, these MOE are measured independently of traffic control system data. Box and Oppenlander (94) provide techniques and sample size requirements for performing many of these studies.
In some cases, these studies may use data generated by the traffic system. It then becomes important to:
• Identify the measurement error for these variables, and
• Specify and collect a sample size which assures statistically significant results. Evaluation procedures must also consider the demand element. The evaluation must account for:
• Changing traffic demands between the before and after period, • Other factors such as weather.
References
1. Kessman, R. “Urban Traffic Control System First Generation Fortran IV Overlay Software (Extended Version).” Volume 1-6, May 1979.
2. Gordon, R.L. “Surveillance and Traffic Responsive Control for First Generation UTCS.” 1987.
3. “Manual of Uniform Traffic Control Devices for Streets and Highways.” Federal Highway Administration, Washington, DC, 2003.
4. Kell, J.H., and I.J. Fullerton. “Manual of Traffic Signal Design.” Institute of Transportation Engineers, Prentice-Hall, Inc., Englewood Cliffs, NJ, 1998.
5. Fullerton, I.J., and J.H. Kell. “Traffic Control Devices Handbook.” Institute of Transportation Engineers, 2001.
6. Asante, S.A., S.A. Ardekani, and J.C. Williams. “Selection Criteria for Left-Turn Phasing, Indication Sequence and Auxiliary Sign.” HPR Research Report 1256- IF, University of Texas at Arlington, Arlington, TX, February 1993.
7. Greenshields, B.D. “Traffic Performance at Urban Street Intersection.” Technical Report No. 1, Yale Bureau of Highway Traffic, New Haven, CT, 1947.
8. Chang, E.C. “Guidelines for Actuated Controllers in Coordinated Systems.” Transportation Research Record 1554, pp. 61-73, Transportation Research Board, Washington, DC, 1996.
9. “Signal and Lighting Design Course Workbook – June 1999.” Minnesota DOT Office of Traffic Engineering, Minneapolis, MN, 1999.
10. “Highway Capacity Manual.” Transportation Research Board, National Research Council, Washington, DC, 2000.
11. Pline, J.L. (editor). “Traffic Engineering Handbook, 5th Edition.” Institute of Transportation Engineers, Washington, DC, 2000.
12. Pignataro, L.J. “Traffic Engineering Theory and Practice.” Prentice-Hall, Inc., Englewood Cliffs, NJ, 1973.
13. Drew, D.R. “Design and Signalization of High-Type Facilities.” Traffic Engineering. Vol. 33, No. 7, pp. 17-25, 1963.
14. Gordon, R.L. “Systems Engineering Processes for Developing Traffic Signal Systems.” NCHRP Synthesis 307, Transportation Research Board, Washington, DC, 2003.
15. Robertson, D.I. “TRANSYT: A Traffic Network Study Tool.” Road Research Laboratory Report No. RL-253, Grothorne, Berkshire, England, 1969.
16. Wallace, C.E, K.G. Courage, D.P. Reaves, G.W. Schoene, G.W. Euler, and A. Wilbur. “Transyt-7F User's Manual.” University of Florida, October 2003.
17. Skabardonis, A., R.L. Bertini, and B.R. Gallagher. “Development and Application of Control Strategies for Signalized Intersections in Coordinated Systems.” Transportation Research Record 1634, pp. 110-117. Transportation Research Board, Washington, DC, 1998.
18. Robertson, D.L., and P.B. Hunt. “A Method of Estimating the Benefits of Coordinating Signals by TRANSYT and SCOOT.” Traffic Engineering and Control, Vol. 23, No. 11, pp. 527-531, 1982.
19. Christopher, P., and R. Kiddle. “Ideal Street Spacing Tables for Balanced Progression.” Federal Highway Administration Report No. FHWA-RD-79-28, Washington, DC, May 1979.
20. Wilshire, R., R. Black, R. Grochoske, and J. Higinbotham. “Traffic Control Systems Handbook.” Federal Highway Administration Report FHWA-1P-85-17, Washington, DC, 1985.
21. Orcutt, F.L., Jr. “The Traffic Signal Book.” Prentice Hall, Englewood Cliffs, NJ, 1993.
22. Chang, E.C.P., and C.J. Messer. “Warrants for Interconnection of Isolated Traffic Signals.” Report 293-1F, Texas Transportation Institute, College Station, TX, August 1986.
23. Freeman, W.J., K,Y. Ho, and E.A. McChesney. “An Evaluation of Intersection System Analysis Techniques.” Presented at the 78th Annual Meeting of the Transportation Research Board, Washington, DC, 1999.
24. Benekohal, R.F., Y.M. Elzohairy, and J.E. Saak. “A Comparison of Delay from HCS, Synchro, Passer II, Passer IV, and Corsim for an Urban Arterial.” Presented at the 81st Annual Meeting of the Transportation Research Board, Washington, DC, 2002.
25. Fambro, D.B., C.A. Lopez, and S.R. Sunkari. “Benefits of the Texas Traffic Light Synchronization ITLS.” Grant Program I: Volume I Report, TXDOT TTI 0258-1, October 1992.
27. “Signal Timing Optimization Software.” 2003. Texas Transportation Institute. <http://ttisoftware.tamu.edu/>.
28. “The Highway Capacity Manual (HCM) version of aaSIDRA.” Akcelik & Associates. <http://www.aatraffic.com/SIDRA/aaSIDRA_HCMversion.htm> 29. “Task D Technical Memorandum, Methodologies for Scoping ITS.” Dunn
Engineering Associates, New York State Department of Transportation, January 2003.
30. Wagner, F.A., D.L. Gerlough, and F.C. Barnes. “Improved Criteria for Traffic Signal Systems on Urban Arterials.” National Cooperative Highway Research Program Report 73, Transportation Research Board, Washington, DC, 1969. 31. Polanis, S.F. “Signal Coordination and Fuel Efficiency; Winston-Salem’s
Experience.” Transportation Quarterly, Vol. 38, No. 2, 1984.
32. Wagner, F.A., “Energy Impacts of Urban Transportation Improvements.” Institute of Transportation Engineers, August 1980.
33. “Urban Traffic Control System Fortran IV Software Documentation.” TRW Transportation and Environment Operations, September 1973.
34. Sperry Systems Management Division, Report Series on UTCS. Federal Highway Administration Reports:
FHWA-RD-73-9TUTCS/BPST Design and Installation FHWA-RD-76-183TUTCS/BPST Operator's Manual FHWA-RD-76-184TUTCS/BPST Maintenance Manual
FHWA-RD-76-160TUTCS/BPST Operations and Maintenance Manual FHWA-RD-76-185TUTCS/BPST Software Manual Vol. 1
FHWA-RD-76-186TUTCS/BPST Software Manual Vol. 2
35. “The Urban Traffic Control System in Washington, D.C.” Federal Highway Administration, U.S. Department of Transportation, Washington DC, (Undated information brochure).
36. Kessman, R. “Urban Traffic Control System First Generation Fortran IV Overlay Software (Extended Version).” Volume I-G, May 1979.
37. Honeywell Inc. - Series of Documents, 1987
FHWA-IP-87-11, Enhanced UTCS Software - Data Base Specifications FHWA-IP-87-12, Enhanced UTCS Software - Operator's Manual
FHWA-IP-87-13, Enhanced UTCS Software - System Software Specification - Vol. 1
FHWA-IP-87-14, Enhanced UTCS Software - System Software Specification - Vol. 2
FHWA-IP-87-15, Enhanced UTCS Software - System Software Specification - Vol. 3
38. Balke, K.N., S.R. Keithreddipalli, and C.L. Brehmer. “Guidelines for Implementing Traffic Responsive Mode in TXDOT Closed Loop Traffic Signal Systems.” Texas Transportation Institute Research Report 2929-3F, College Station, TX, August 1997.
39. Hunt, P.B., D.I. Robertson, R.D. Bretherton, and R.I. Winton. “SCOOT - A Traffic Responsive Method of Coordinating Signals.” Transport and Road Research Laboratory Report, LR-1014. Crawthorne, Berkshire, England, 1981. 40. Hunt, P.B., D.I. Robertson, R.D. Bretherton, and M.C. Rogle. “The SCOOT On-
Line Traffic Signal Optimization Technique.” Traffic Engineering and Control, pp. 190-199, April 1982.
41. Robertson, D.I., and R.D. Bretherton. “Optimizing Networks of Traffic Signals in Real Time - The SCOOT Method.” IEEE Transactions on Vehicular Technology, Vol. 40, No. 1, pp. 11-15, February 1991.
42. Bretherton, R.D., and G.T. Bowen. “Recent Enhancements to SCOOT - SCOOT Version 2.4.” Road Traffic Control, Institution of Electrical Engineers, London, 1990.
43. Bretherton, D., G. Bowen, K. Wood. “Effective Urban Traffic Management and Control.” Presented at 82nd Annual Transportation Research Board Meeting, Washington, DC, 2003.
44. Lowrie, P.R. “SCATS - Sydney Co-Ordinated Adaptive Traffic System - A Traffic Responsive Method of Controlling Urban Traffic.” Roads and Traffic Authority, Sydney, NSW, Australia, September 1992.
45. Michalopoulis, P.G., R.D. Jacobson, C.A. Anderson, and J.C. Barbaresso. “Field Deployment of Autoscope in the Fast-Trac ATMS / ATIS Programme.” Traffic Engineering and Control, pp. 475-483, September 1992.
46. Gross, N. R., “SCATS Adaptive Traffic System.” TRB Adaptive Traffic Control Workshop. Transcore, January 2000 <http://signalsystems.tamu.edu/documents/ TRBWorkshop2000/SCATS_TRB2000Pres2.pdf>.
47. Zabrieszach, D., and P. Petridis, “Deployment of SCATS 2 in Melbourne, Australia.” 25th Australian Research Forum, Incorporating the BTRE Transport Policy Colloquium. Canberra, Australia, October 2002 <http://www.btre.gov.au/
48. City of Troy, Michigan, “SCATS Traffic Signal System.” August 2000 <http://www.ci.troy.mi.us/TrafficEngineering/sindex.htm>.
49. Abdel-Rahim, A., et. al. “The Impact of SCATS on Travel Time and Delay.” 8th ITS America Annual Meeting, Detroit, MI, May 1998 <http://www.benefitcost. its.dot.gov/its/benecost.nsf/ID/AF5E7F6989F1A500852569610051E2E6?OpenD ocument&Flag=Country>.
50. Head, K.L., P.B. Mirchandani, and S. Shelby. “The Rhodes Prototype: A Description and Some Results.” Presented at the 77th Annual meeting of the Transportation Research Board, Washington, DC, 1998.
51. Gartner, N.H., F.J. Poorhan, and C.M. Andrews. “Implementations and Field Testing of the OPAC Adaptive Control Strategy in RT-TRACS.” Presented at the 81st Annual Meeting of the Transportation Research Board, Washington, DC, 2002.
52. Pignataro, L.J. “Traffic Control in Oversaturated Street Networks.” National Cooperative Highway Research Program Report 194. Transportation Research Board, Washington, DC, 1978.
53. Quinn, D.J. “A Review of Queue Management Strategies.” Traffic Engineering and Control, November 1992.
54. Rathi, A.K. “A Control Scheme for High Traffic Density Sectors.” Transportation Research, 22B(2), pp. 81-101, 1988.
55. “Internal Metering Policy for Oversaturated Networks.” Volumes 1 and 2, KLD Associates and Texas Transportation Institute, June 1992, NCHRP 3-38 (4).
56. Lieberman, E.B., J. Chang, and E.S. Prassas. “Formulation of a Real-Time Control Policy for Oversaturated Arterials.” presented at the 79th Annual Meeting of the Transportation Research Board, Washington, DC, 2000.
57. Abu-Lebdeh, G., and R.F. Benekohal, “Development of Traffic Control and Queue Management Procedure for Over-Saturated Arterials.” Transportation Research Record 1603, Transportation Research Board, Washington, DC.
58. Park, B., C.J. Messer, and T. Urbanik. “Traffic Signal Optimization Program for Over-Saturated Conditions, Genetic Algorithm Approach.” Transportation Research Record 1683, pp. 133-142, Transportation Research Board, Washington, DC, 1999.
59. Girianna, M., and R.F. Benekohal. “Dynamic Signal Coordination for Networks with Oversaturated Intersections.” presented at the 81st Annual Meeting of the Transportation Research Board, Washington, DC, 2002.
60. Girianna, M., and R.F. Benekohal. “Signal Coordination for a Two-Way Street network With Oversaturated Intersections.” presented at the 82nd Annual Meeting of the Transportation Research Board, Washington, DC, 2003.
61. Smeed, R.J. “Road Capacity of City Centers.” Traffic Engineering and Control, pp. 455-458, November 1966.
62. Godfrey, J.W. “The Mechanism of a Road Network.” Traffic Engineering and Control, pp. 323-327, November 1969.
63. Kennedy, R. “The Day the Traffic Disappeared.” The New York Times Magazine, pp 42-45, April 20, 2003.
64. “Transport for London.” <https://www.cclondon.com/WebCenterBrandedTR4/ StaticPages/index.aspx>.
65. “Traffic Software Integrated System.” Federal Highway Administration <http://www.fhwa-tsis.com>.
66. “Paramics Online.” Quadstone Limited <http://www.paramics-online.com/ contact/index.htm>.
67. “ITC – World.” <http://www.itc-world.com/vissim.htm>.
68. Nelson, E.J., D. Bullock, and T. Urbanik. “Implementing Actuated Control of Diamond Interchanges.” Journal of Transportation Engineering, Vol. 126, No. 5,